---
license: apache-2.0
base_model: Harveenchadha/hindi_base_wav2vec2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hindi_wav2vec2_optimized_2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hindi_wav2vec2_optimized_2

This model is a fine-tuned version of [Harveenchadha/hindi_base_wav2vec2](https://huggingface.co/Harveenchadha/hindi_base_wav2vec2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6089
- Wer: 0.1899

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2406        | 5.56  | 25   | 0.5544          | 0.3418 |
| 0.0725        | 11.11 | 50   | 0.4668          | 0.2426 |
| 0.0437        | 16.67 | 75   | 0.6185          | 0.2405 |
| 0.0344        | 22.22 | 100  | 0.5553          | 0.2257 |
| 0.0311        | 27.78 | 125  | 0.5775          | 0.2300 |
| 0.0287        | 33.33 | 150  | 0.7120          | 0.2110 |
| 0.0242        | 38.89 | 175  | 0.7068          | 0.2152 |
| 0.0175        | 44.44 | 200  | 0.5265          | 0.2384 |
| 0.0128        | 50.0  | 225  | 0.5554          | 0.2300 |
| 0.0114        | 55.56 | 250  | 0.6330          | 0.2300 |
| 0.0105        | 61.11 | 275  | 0.6020          | 0.2194 |
| 0.0052        | 66.67 | 300  | 0.6073          | 0.2152 |
| 0.0041        | 72.22 | 325  | 0.5865          | 0.1941 |
| 0.0074        | 77.78 | 350  | 0.6138          | 0.1983 |
| 0.0033        | 83.33 | 375  | 0.6106          | 0.1920 |
| 0.0074        | 88.89 | 400  | 0.6089          | 0.1899 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1